Data Methodology

© 2010 MediaMind Technologies Inc. | All rights reserved

Itzik Mitzmacher | Program Manager

January 2011

Data MethodologyResearch Module

© 2010 MediaMind Technologies Inc. | All rights reserved© 2010 MediaMind Technologies Inc. | All rights reserved

▸ The Data Funnel

▸ Frequently Asked Questions

▸ Q&A

Agenda


The Universe (DWH)

Monthly Aggregation

Data Massaging

Result

The Data Funnel

Measurement Types• Ad-Centric• User-Centric

Thresholds• Ensure statistical

soundness• Protect confidential infoFilter Criteria


Frequently Asked Questions


Hey, the data is mine. How come you share my

own data with all your clients?“

”


Data Ownership

▸ We are not sharing data. This is simply a research for the purpose of creating benchmarks, which is something we have been doing for years (e.g. Analytics benchmarks).

▸ It is a legal practice. In its standard agreement with agencies, MediaMind keeps the right to use the data it tracks and collects for research purpose on an aggregated level (i.e. benchmarks).

What if my client is concerned about “free riders” (small clients enjoying a large amount of data contributed by one single advertiser)?

▸ MediaMind collects data from more than 7000 advertisers. The “free rider” issue is only theoretical. That said, we make sure to avoid situations where one advertiser contributes all the data. Refer to the next item.

What if my client is still not convinced?

▸ It’s possible that sometimes clients will react in an irrational manner. If that’s the case make sure to escalate the issue.


Hey, how do you make sure that the data presented in Smart Planning will not

expose any confidential info to competing agencies or

advertisers?

“”


Data Confidentiality

▸ Cost data - no cost data is aggregated and shared across agencies. Wherever there is a cost metric (Avg. CPM, CPC, etc.), it is always based on the agency’s data only.

▸ Performance and engagement data – the user can see only a benchmark. We don’t tell the user where the data came from and the user has no way to back out confidential data.

▸ In addition, we apply filters on the backend to ensure that we’re not creating the benchmarks based on a limited amount of data that will allow the user to back out confidential data about competitors. So, for example, if the user filters to Market = UK | Vertical = CPG, we will not provide info on the screen if there are not enough advertisers/campaigns/data to base the benchmarks on.

▸ If the user chooses to drill down to a specific agency or advertiser level then he will be able to select only his own agency or advertisers for which the user has a permission to see data in MediaMind.


Hey, how do you make sure statistical outliers

won’t skew the benchmark up or down?“

”


Data Accuracy

▸ Our thresholds should protect us from these cases. In each search the user conducts, we apply thresholds that dictate that no result will be retrieved if there’s not enough data to make the benchmark statistically significant.

▸ Here are few examples to the thresholds that we apply:

• Each figure represents a minimum of 10,000 impressions spread across different ads, campaigns and advertisers.

• Each ad is served a minimum of 1,000 impressions.

• Data was filtered for outliers, which represent a divergence from regular campaign performance according the MediaMind data.


Thank you!

Documents

Data Methodology